I need to identify the main categorical columns in this dataset and find their most common values with frequencies. Let me start by getting the column metadata to understand what categorical columns exist. ```json { "action": "tool_call", "reasoning": "I need to see the column metadata to identify which columns are categorical (VARCHAR/TEXT type with reasonable cardinality). The dataset card shows columns_catalog is the largest table, but I should look at the analytics.column_overview metadata to get a comprehensive view of all categorical columns across tables.", "tool": "query_sql", "args": { "sql": "SELECT table_name, column_name, phys_type, semantic_role, rough_kind, distinct_count, approx_distinct_count FROM analytics.column_overview WHERE phys_type IN ('VARCHAR', 'TEXT') AND approx_distinct_count < 1000 ORDER BY approx_distinct_count DESC LIMIT 50", "purpose": "Identify main categorical columns across all tables by finding VARCHAR/TEXT columns with manageable cardinality (< 1000 distinct values)", "source": "raw" } } ```